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Effect of articulatory Δ and ΔΔ parameters on multilayer neural network based speech recognition.

, , , , , , , и . APCCAS, стр. 624-627. IEEE, (2010)

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Prabhakar Kotwal

Masoom Alam

Homayun Alam

Fakhrul Alam

Nima Alam

 

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DPF-based japanese phoneme recognition using tandem MLNs., , , , , , , и . HIS, стр. 209-212. IEEE, (2010)Bangla triphone HMM based word recognition., , , , , , , и . APCCAS, стр. 883-886. IEEE, (2010)Local Feature or Mel Frequency Cepstral Coefficients - Which One Is Better for MLN-Based Bangla Speech Recognition?, , , , , и . ACC (2), том 191 из Communications in Computer and Information Science, стр. 154-161. Springer, (2011)Recurrent Neural Network Based Phoneme Recognition Incorporating Articulatory Dynamic Parameters., , , , , и . ACC (3), том 192 из Communications in Computer and Information Science, стр. 349-356. Springer, (2011)Extraction of Local Features for Tri-Phone Based Bangla ASR., , , , и . ITNG, стр. 668-673. IEEE Computer Society, (2012)Local Feature or Mel Frequency Cepstral Coefficients - Which One is Better for MLN-Based Bangla Speech Recognition?, , , , , и . CoRR, (2013)Hybridization of two stage Multilayer Neural Networks based Bangla ASR incorporating dynamic parameters., , , и . HIS, стр. 167-172. IEEE, (2011)Phone Segmentation for Japanese Triphthong Using Neural Networks., , , , , и . ITNG, стр. 470-475. IEEE Computer Society, (2011)Effect of articulatory Δ and ΔΔ parameters on multilayer neural network based speech recognition., , , , , , , и . APCCAS, стр. 624-627. IEEE, (2010)